Improvements of real coded genetic algorithms based on differential operators preventing premature convergence
نویسندگان
چکیده
منابع مشابه
Improvements of real coded genetic algorithms based on differential operators preventing premature convergence
This paper presents several types of evolutionary algorithms (EAs) used for global optimization on real domains. The interest has been focused on multimodal problems, where the difficulties of a premature convergence usually occurs. First the standard genetic algorithm (SGA) using binary encoding of real values and its unsatisfactory behavior with multimodal problems is briefly reviewed togethe...
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The definition of the hardness of a problem for GA’s has been tackled, eventually leading to the notion of deception [Gol89, HG94, Dav87]. It has been known for a while that the hardness of a problem is inherently related to the representation that is used. This fact will be illustrated below by showing that an easy problem (1’s counting problem) can become nearly unsolvable after a change of r...
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Most real-coded genetic algorithm research has focused on developing effective crossover operators, and as a result, many different types of crossover operators have been proposed. Some forms of crossover operators are more suitable to tackle certain problems than others, even at the different stages of the genetic process in the same problem. For this reason, techniques that combine multiple c...
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Genetic algorithms are adaptive methods which may be used as approximation heuristic for search and optimization problems. Genetic algorithms process a population of search space solutions with three operations: selection, crossover and mutation. A great problem in the use of genetic algorithms is the premature convergence, a premature stagnation of the search caused by the lack of diversity in...
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ژورنال
عنوان ژورنال: Advances in Engineering Software
سال: 2004
ISSN: 0965-9978
DOI: 10.1016/s0965-9978(03)00113-3